GSEA分析

GSEA.png

myfiles <- list.files(pattern = "*.csv")
myfiles
matrix<-read.csv(myfiles[1],sep=',',header=T,check.names=F)
library('clusterProfiler') 
library('org.Mm.eg.db')
ENTREZID<- bitr(matrix$Row.names, fromType = "ENSEMBL", 
                toType=c('SYMBOL',"ENTREZID","GENENAME"),
                OrgDb = org.Mm.eg.db, drop = FALSE)
ENTREZID=ENTREZID[!duplicated(ENTREZID$ENTREZID),]#去除重复的ENSEMBL
data <- data.frame(Row.names=ENTREZID$ENSEMBL,
                   SYMBOL=ENTREZID$SYMBOL,
                   entrezgene_id=ENTREZID$ENTREZID,
                   description=ENTREZID$GENENAME)
data1 <-merge(data,matrix,by="Row.names")
testdata <-subset(data1,entrezgene_id!= 'NA')
## 1.获取基因logFC
geneList <- testdata$log2.FC.
## 2.命名
names(geneList) = testdata$entrezgene_id
## 3.排序很重要
geneList = sort(geneList, decreasing = TRUE)
head(geneList)
gseaKEGG <- gseKEGG(geneList     = geneList,
                    organism     = 'mmu',
                    nPerm        = 5000,
                    minGSSize    = 10,
                    pvalueCutoff = 0.05,
                    verbose      = FALSE)

气泡图

library(ggplot2)
dotplot(gseaKEGG,showCategory=20,split=".sign")+facet_grid(~.sign)

Fig1.png

gseaKEGG_results <- gseaKEGG@result
View(gseaKEGG_results)

GSEA分析

library(enrichplot)
pathway.id = "mmu04080"
gseaplot2(gseaKEGG, 
          color = "red",
          geneSetID = pathway.id,
          pvalue_table = T)

pathway.id = "mmu00980"
gseaplot2(gseaKEGG, 
          color = "#DAB546",
          geneSetID = pathway.id,
          pvalue_table = T)
gseaplot2(gseaKEGG, 
          color = "blue",
          geneSetID = pathway.id,
          pvalue_table = T)

通路具体化

library(pathview)
pathway.id = "mmu04110"
pv.out <- pathview(gene.data  = geneList,
                   pathway.id = pathway.id,
                   species    = "mmu")

mmu04151.pathview.png